Reduce Readmissions and Improve Outcomes with Automated Analytics

Emcien’s predictive analytics solutions are a perfect fit for healthcare systems looking to improve outcomes and reduce readmission rates. Healthcare data is complex and varied, including demographics, treatment, insurance data, and much more. Some of this data is numeric, but much of it is categorical, semi-structured, or unstructured. Trying to make sense of all this data is difficult, but it’s even more difficult to conduct an analysis that will impact patient outcomes.

Using EmcienScan for data discovery, analysts automatically identify what data will important for each target outcome. This initial view automates what is often the most costly and time-consuming parts of data analysis, identifying connections across data to guide the analysis.

Predicting Readmission

With the right data identified in the discovery phase, EmcienPatterns then performs a deeper analysis to discover the precise combinations of data points that predict the target outcome. Out of hundreds of different data points that can be collected on patients, it’s the different combinations of factors that affect the final outcome, and EmcienPatterns is designed to differentiate between those combinations to create the most accurate predictions. For each patient the system then makes a prediction on the likely outcome and the reasons for that prediction, guiding administrators to next best action.

With these predictive rules, providers can:

  • Identify combinations of events from across EMR and patient journeys that indicate high likelihood of readmisssion.
  • Predict which patients are more likely to require more resources.
  • Get a cross-continuum of care view of patients’ data, treatment, and outcomes.
  • Highly targeted interventions.

Business Value:

  • Improve outcomes by identifying high-cost patients early.
  • Reduce costs associated with readmission penalties.

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